The subject matter disclosed herein relates generally to data reconstruction systems and methods, and more particularly to systems and methods to reconstruct data in soft-field tomography.
Soft-field tomography, such as Electrical Impedance Spectroscopy (EIS) (also referred to as Electrical Impedance Tomography (EIT)), diffuse optical tomography, elastography, and related modalities may be used to measure the internal properties of an object, such as the electrical properties of materials comprising internal structures of an object (e.g., a region of a human body). For example, in EIS systems, an estimate is made of the distribution of electrical conductivities of the internal structures. Such EIS systems reconstruct the conductivity and/or permittivity of the materials within the area or volume based on an applied excitation (e.g., current) and a measured response (e.g., voltage) typically acquired at a surface of the area or volume. Visual distributions of the estimates can then be formed.
In EIS, the complex conductivity distributions within a volume are determined using assumed known applied electrical excitations, apriori geometry and surface electrode data, and signal measurement data from transducers coupled to the volume under test. An electromagnetic model with assumptions about the volume and electrode geometry, boundary conditions, the applied excitation, and the interior conductivity distribution are then used to determine a predicted response to a given excitation. The inverse problem in EIS is to determine the spatial distribution of complex conductivities that give rise to the difference between measured data and the predicted model data.
The EIS inverse problem is highly ill-posed in that large perturbations in the conductivity distribution may result in small changes in the measurement data. Similarly, small changes or errors in the applied excitation may result in large changes in the measured data. In some applications, such as stroke detection, the signal-to-noise ratio may be too low to accurately identify the impedances.
Conventional EIS is performed using a single measurement or determining a difference between two measurements to provide reconstruction localization or image generation. However, in some environments, for example in a hospital environment, estimates of the temporal behavior of impedance changes over time can be useful, such as for patient monitoring.